Aircraft Surface State Event Track System and Method

ABSTRACT

A method, executed by a processor, includes the processor receiving signals information from a device located on a departing airplane; verifying an identification of the airplane and identifying an expected departure sequence of aircraft surface states; monitoring and identifying additional signals information received from the mobile device, including comparing the additional signals information to known data; logging the additional signals information, and processing the additional signals information, and determining the logged data corresponds to events indicative of an aircraft surface state; sending an aircraft surface state reached message to Local and Center flight management; and executing a statistical routine and providing statistical data from the execution relating to an occurrence of upcoming aircraft surface state event and sending the statistical data with the aircraft surface state message.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/588,574, filed May 5, 2017, and entitled AIRCRAFT SURFACE STATE EVENTTRACK SYSTEM AND METHOD, the disclosure of which is incorporated byreference.

BACKGROUND

Air traffic control uses a complex regime of systems, methods, rules,and procedures, some dictated by government agencies, to ensure safe andefficient movement of aircraft, on the ground and in the air. One aspectof this regime involves evaluation of aircraft-related events at adeparture airport to predict events at an arrival airport. For example,whether an airplane makes its arrival slot may depend on whether thesame airplane departed on time. Whether an airplane makes its scheduleddeparture time may depend on events that occur on movement andnon-movement areas of the departure (origination) airport.

One example procedure currently in use in this regime is that, aftertakeoff, aircraft may be directed to merge into en route (Center)airspace traffic flows—the aircraft are “metered.” (In air trafficcontrol, an Area Control Center (ACC), also known as a Center (or insome cases, en-route, as opposed to TRACON control), is a facilityresponsible for controlling aircraft en route in a particular volume ofairspace (a Flight Information Region) at high altitudes between airportapproaches and departures. Such a Center also may be referred to as anAir Route Traffic Control Center (ARTCC).) Departure and arrivalairports may be in the same Center, or in separate Centers. In somecases, constraints associated with these Center traffic flows createlocalized demand/capacity imbalances—that is, demand for space or slotsin a Center traffic flow exceeds capacity of the Center traffic flow.When demand exceeds capacity, Traffic Management Coordinators (TMCs) ata Center and Frontline Managers (FLMs) at a Local airport may use aprocedure referred to as tactical departure scheduling to manage theflow of departures into the constrained Center traffic flow. Tacticaldeparture scheduling usually involves a Call for Release (CFR) procedurein which a Local air traffic control (i.e., at a Local airport Tower)calls the Center to coordinate an aircraft release time prior toallowing the aircraft to depart. Currently, release times are computedat the Center using a Center Traffic Management Advisor (TMA) decisionsupport tool, based upon manual estimates of aircraft ready time thatare verbally communicated from the Tower to the Center. The TMA-computedrelease time then is verbally communicated from the Center back to theTower where the release time is relayed to the Local air trafficcontroller as a release window, which typically is three minutes wide.The Local air traffic controller manages aircraft departure to meet thecoordinated release time window. Manual ready time prediction by theLocal air traffic controller and verbal release time coordinationbetween the Local and Center are labor intensive and prone toinaccuracy. Also, use of release time windows adds uncertainty to thetactical departure process. Currently, many tactically-scheduledaircraft miss their en route slot due to ready time predictionuncertainty.

Furthermore, about 25% of arrival-metered aircraft involve a tacticaldeparture. This means that 25% of inbound flights metered by an arrivalTMA system (i.e., at an Arrival Center) are scheduled (i.e., have slotsreserved) in the overhead stream while the aircraft still are on thesurface at the departure airport. An emerging demand for tacticaldeparture scheduling and the significant uncertaintytactically-scheduled aircraft represent to the en route schedule,increases the importance of integrating departure airport surfaceinformation into departure scheduling.

The Aircraft Communications Addressing and Reporting System (ACARS),introduced in 1978, provided a digital datalink system for transmissionof short messages between aircraft and ground stations via airband radioor satellite. One aspect of ACARS is the ability to automatically detectand report the start of each major flight phase, called OOOI (out of thegate, off the ground, on the ground, and into the gate). About 70% ofU.S. commercial flights involve OOOI events. These OOOI events aredetected using input from aircraft sensors mounted on doors, parkingbrakes, and struts. At the start of each flight phase, an ACARS messageis transmitted to the ground describing the flight phase, the time atwhich it occurred, and other related information such as the amount offuel on board or the flight origin and destination. These messages areused to track the status of aircraft and crews. However, ACARS cannotpredict whether an airplane will meet its scheduled states, such asdeparture states gate pushback, runway entry, and takeoff, and ACARSdoes not provide information that allows Center and Local flightmanagement personnel to coordinate aircraft departure and therebyimprove departure slot performance.

Airport surface surveillance using traditional radar-based ormultilateration systems have the potential to improve departure slotperformance, but may not be a viable option. Airport surfacesurveillance systems are very expensive to procure, install, andmaintain. The high cost makes these surface surveillance systemsimpractical for most airports. Furthermore, surveillance in an airport'snon-movement presents additional challenges such as limitedline-of-sight and multipath interference caused by buildings and otherstructures. Still further, the FAA is responsible for movement areas ofan airport while the airport is responsible for non-movement areas, andthe FAA does not surveil the non-movement areas, and does not usenon-movement area surveillance. Other complications lessen thereliability of current surface surveillance systems.

SUMMARY

A method, executed by a processor, includes the processor receivingsignals information from a device located on a departing airplane;verifying an identification of the airplane and identifying an expecteddeparture sequence of aircraft surface states; monitoring andidentifying additional signals information received from the mobiledevice, including comparing the additional signals information to knowndata; logging the additional signals information, and processing theadditional signals information, and determining the logged datacorresponds to events indicative of an aircraft surface state; sendingan aircraft surface state reached message to Local and Center flightmanagement; and executing a statistical routine and providingstatistical data from the execution relating to an occurrence ofupcoming aircraft surface state event and sending the statistical datawith the aircraft surface state message.

A non-transitory, computer-readable storage medium having encodedthereon machine instructions that when executed by a processor, causethe processor to receive signals information from a device located on adeparting airplane; verify an identification of the airplane andidentify an expected departure sequence of aircraft surface states;monitor and identify additional signals information received from themobile device, wherein the processor: compares the additional signalsinformation to known data; logs the additional signals information, andprocesses the additional signals information, and determines the loggeddata corresponds to events indicative of an aircraft surface state;sends an aircraft surface state reached message to Local and Centerflight management; and executes a statistical routine and providesstatistical data from the execution relating to an occurrence ofupcoming aircraft surface state event and sending the statistical datawith the aircraft surface state message.

An aircraft surface state event track (ASSET) system, comprises a mobiledevice installed on an aircraft, the mobile device comprising sensors torecord signals information indicative or operation of the aircraft; anda processor in communication with the mobile device. The processorexecutes machine instructions to receive signals information from themobile device, identify the signals information received from the mobiledevice, compare the identified signals information to known data, basedon the comparison, determine the aircraft is at a defined aircraftsurface state, send an aircraft surface state reached message to Localand Center flight management; and execute a statistical routine andprovide statistical data from the execution relating to an occurrence ofupcoming aircraft surface state and send the statistical data with theaircraft surface state message.

DESCRIPTION OF THE DRAWINGS

The detailed description refers to the following figures in which likenumerals refer to like items, and in which:

FIG. 1A shows a profile and time line of events that occur duringtake-off of a tactically-scheduled aircraft;

FIG. 1B illustrates a National Airspace System (NAS) environment inwhich departing aircraft must enter a metered time slot;

FIG. 1C illustrates an airport environment in which an example surfacestate event track system, and corresponding method, may be implemented;

FIG. 1D illustrates, logically, communication flows for departure of atactically-scheduled aircraft;

FIG. 2A illustrates an example aircraft surface state event tracksystem;

FIGS. 2B-2D illustrate alternate examples of an aircraft surface stateevent track system; and

FIGS. 3A-3B illustrate example methods executed by the aircraft surfacestate event track system of FIG. 2A.

DETAILED DESCRIPTION

At airports large and small, safe and efficient aircraft trafficmanagement requires accurate information about aircraft on the airportsurface, from gate to runway. However, only a few U.S. airports havesurface surveillance systems, and in almost every case coverage islimited to the airport's movement area. In addition, safe and efficientaircraft traffic management requires accurate and timely aircraftarrival information, and such arrival information may be affected byaircraft events that occur at the aircraft's departure (originating)airport.

In addition to improving airport safety by preventing incidents betweenand among moving aircraft and between and among moving aircraft andground vehicles, a surface surveillance system also may improve airportefficiency by ensuring that scheduled aircraft arrivals and departuresoccur with minimal delays and at minimal intervals consistent withsafety. For example, an airport may adopt a time-based flow management(TBFM) system that ensures efficient (i.e., on-time or on schedule)aircraft departure considering on-time considerations for aircraftarrival. That is, an aircraft's departure time may need to be met toensure the aircraft's arrival fits into a crowded aircraft arrivalstream. If the departing aircraft is not able to take off within itsscheduled departure slot, a corresponding slot in the arrival stream maygo unused. A series of missed departures slots can result in runwaystarvation, resulting in wasted resources, additional arrival and/ordeparture delays and frustrated travelers.

While airports have installed surface surveillance systems to addressthe above noted concerns, only 43 of the more than 500 “towered”airports in the U.S. National Airspace System (NAS) have surfacesurveillance and only a small fraction of those have non-movement areasurveillance. Furthermore, the only U.S. airport with an operationaldeparture management system (DMS) is JFK International Airport (JFK).The JFK DMS uses one surveillance system for movement area (e.g.,runway, taxiway) surveillance and another surveillance system for theairport's non-movement area (i.e., areas on which aircraft may be found,other than runways and taxiways). At JFK, a departure coordinator mayuse the non-movement area surveillance to verify a flight will meet itsintended time to enter the movement area (i.e., in preparation fortakeoff). If the airline provides an estimated time for gate pushback,the departure coordinator could use non-movement area surveillance todetermine whether a flight likely will meet its target movement areaarrival time. If the aircraft is late departing the gate, the departurecoordinator may change the departure sequence to minimize missed runawayopportunities. However, without non-movement area surveillance data, thedeparture coordinator may not be able to accurately estimate if theaircraft will meet its target movement area arrival time. Missedmovement area arrival times create holes or inefficiencies in thedeparture sequence resulting in suboptimal runway use.

To address efficient airport operations while maintaining requiredsafety, disclosed herein are systems and methods that may improveairport departure and arrival performance, regardless of airport size,without the installation and maintenance of expensive and complicatedautomated surface surveillance systems, such as those at JFK. Thesystems and methods determine aircraft surface state at several pointsin a departure sequence. The systems and methods further provide aconfidence interval and/or level that certain of the states will bereached or achieved at an expected time. The occurrence of the statesand corresponding confidence intervals and levels are passed to Localair traffic control and other flight management personnel and systems.This information then may be passed to Center flight managementpersonnel and systems. The information thus passed allows flightmanagement personnel and systems to assess if a departing aircraft willmeet its intended arrival time, or in the case of metered aircraft, ifthe departing aircraft will reach its designated en route slot.

The herein disclosed systems and methods may refer to the followingterms and their definitions (for some terms, the definition(s) providedcomes from a government agency (e.g., FAA) or a non-government body(e.g., International Civil Aviation Organization (ICAO)); other terms,and their definitions, are provided for ease of description of theherein disclosed inventions), and such references will be understood toincorporate the definitions provided herein for these terms.

Automatic dependent surveillance-broadcast (ADS-B) refers to asurveillance technology in which an aircraft determines its position viasatellite navigation and periodically broadcasts the position, enablingthe aircraft to be tracked. The aircraft position information can bereceived by air traffic control ground stations as well as by otheraircraft to provide situational awareness and allow self-separationbetween and among aircraft. ADS-B is “automatic” in that it requires nopilot or external input. ADS-B is “dependent” in that it depends on datafrom the aircraft's onboard equipment

Airline operations center (AOC) refers to a control center used by aspecific airline or air carrier.

Airport movement area refers to the runways, taxiways, and other areasof an airport that are used for taxiing, takeoff, and landing ofaircraft, exclusive of loading ramps and aircraft parking areas (See 14C.F.R. § 139.3 (Definitions)).

Airport non-movement area refers to aircraft loading ramps and aircraftparking areas; the term “non-movement area” is not defined in 14 C.F.R.§ 139.3.

Airport Surface Detection Equipment, Model X, or (ASDE-X) refers to arunway-safety tool that enables air traffic controllers to detectpotential runway conflicts by providing detailed coverage of movement onrunways and taxiways. By collecting data from a variety of sources,ASDE-X tracks vehicles and aircraft on airport surfaces and obtainsidentification information from aircraft transponders.

Automated airport surveillance system refers to a radar system used atairports to detect and display the position of aircraft in the terminalarea and the airspace around the airport, and may constitute the mainair traffic control system for the airspace around airports. At largeairports, the surveillance typically controls traffic within a radius of30 to 50 nautical miles of the airport.

Center refers to a central flight management entity that may provideregional airspace control and monitoring for several airports. TheCenter may communicate with Local air traffic control and other entitiesat each of its serviced airports and with other Centers.

Center flight management refers to systems, such as the TMA,organizations, and personnel at the Center that operate to manageflights through the airspace under Center supervision.

Commercial off-the-shelf (COTS) refers to commercially availablecomponents that may be incorporated in various airport and aircraftsystems.

Electronic Flight Bag (EFB) refers to an electronic informationmanagement device that helps flight crews perform flight managementtasks more easily and efficiently with less paper. The EFB includes acomputing platform intended to reduce, or replace, paper-based referencematerial often found in the pilot's carry-on flight bag, including theaircraft operating manual, flight-crew operating manual, andnavigational charts (including moving map for air and groundoperations). In addition, the EFB can host purpose-built softwareapplications to automate other functions normally conducted by hand,such as performance take-off calculations. The FAA has defined threedifferent classes of EFB which specify the level of connectivity withthe aircraft and the types of applications that can be run. Class 1 is acommercial off-the-shelf (COTS) mobile device, such as a tablet, thatdoes not connect to the aircraft's systems and does not requirecertification. Class 2 is a portable COTS device that can be temporarilyconnected to the aircraft's power supply, data ports, or antennas. Class3 EFBs are fully installed on the aircraft and must meet airworthinesscertification regulations. An expected revision to the FAA'sclassification scheme will simply categorize EFB as either “Portable” or“Installed”.

Estimated off block time (EOBT) refers to the estimated time an aircraftwill begin movement associated with departure (i.e., move off itsgate/stand).

Freeze horizon refers to the time at which an aircraft's scheduled timeof arrival (STA) at a specific geographical point becomes fixed. Thissetting ensures that last minute changes to the ETA are avoided. Thissetting can be expressed as a prescribed flying time to the meter fix.

Local flight management, or Local air traffic control refers to systems,organizations, and personnel, at a Local airport, that execute processesor supervise systems to control aircraft on the non-movement areas ofthe Local airport and that interface with aircraft during takeoff fromand approach to the Local airport.

Metering times refers to times aircraft are assigned to reach certainpoints, and metering times are an aspect of Time Based Flow Management(TBFM), a tool intended to manage traffic flows by scheduling andspacing aircraft to their arrival airport. (Not all commercial aircraftcurrently are metered.) Through TBFM, an automation system uses aschedule of runway assignments and landing times to sequence inboundflights, and allocates delays to various segments of each flight to meetthe assigned schedule. TBFM is administered by traffic managers at anAir Route Traffic Control Center (ARTCC).

Multilateration refers to a surveillance technology that calculates anaircraft's position from the small differences in timing of when atransponder signal from the aircraft is received by ground antennas. Anytransponder-equipped aircraft can be tracked by multilateration.

Ramp refers to a non-movement area where pre-flight activities, such asparking and maintenance.

Runway, in the parlance of the International Civil Aviation Organization(ICAO), refers to a “defined rectangular area on a land aerodromeprepared for the landing and takeoff of aircraft.”

Surface movement radar (SMR) refers to radar systems used tonon-cooperatively detect objects (e.g., aircraft, vehicles, people,wildlife) on the surface of an airport. Air traffic controllers may useSMR to supplement visual observations. SMR also may be used at night andduring low visibility to monitor the movement of aircraft and vehicles.

Target movement area entry time (TMAT) refers to the time a departingaircraft is planned to transition from the non-movement area of anairport to the movement area. A TMAT is generated as a part of departuresequencing and flight operators plan their departure process in order toachieve that TMAT. TMATs may be specified to meter the rate of departureentries into the movement area of the airport.

Target off block time (TOBT) refers to a point in time to be monitoredand confirmed by the airline/handling agent at which the ground handlingprocess is concluded, all aircraft doors are closed, all passengerboarding bridges have been removed from the aircraft and thus start-upapproval and push-back/taxi clearance can be received.

Terminal radar approach control facility (TRACON) refers to acentralized control station that provides approach and departureservices for one or more airports, including the safe, orderly, andexpeditious flow of arrival, departure, and en-route traffic.

Time-Based Flow Management (TBFM) refers to a FAA program thatimplements a time-based air traffic scheduling and spacing automationtool to optimize aircraft movement.

Traffic Management Coordinator (TMC) refers to an air traffic controlposition, at an en route facility (Center) who is responsible forensuring that efficient and effective traffic management is maintained.

FIG. 1A illustrates a profile 2 and time line 3 of events that occurduring take-off of a tactically-scheduled aircraft. A similar profilemay exist for any aircraft take-off; the main difference being aCoordinated Release Time negotiated between Center and Local flightmanagement personnel. In FIG. 1A, airplane 19A is seen departing from aLocal airport with a Coordinated Release Time. The profile 2 shows aseries of aircraft states and events, all of which occur with some timevariability. The profile 2 begins with a gate pushback event or statefollowed by a spot cross event or state (the airplane 19A leaves theramp and enters a taxiway, for example). Next is Cleared for T/O, whichis the time at which the Local air traffic controller issues a takeoffclearance, and is the time at which control of actual takeoff is cededto the pilot. Ideally, the tower air traffic controller issues thetakeoff clearance so that airplane 19A takes off within a time widow ofthe Coordinated Release Time. However, variability in some of the nextevents may cause the window to be missed. Start of roll occurs at somevariable time after the pilot receives the takeoff clearance. Start ofroll variability results from human factors (i.e., the pilot) andaircraft characteristics. Wheels off (OFF) is the state at which theweight of the airplane 19A comes off its wheels and is the point atwhich the airplane 19A becomes airborne. The time between start of rolland OFF depends largely on meteorological conditions (e.g., temperatureand wind), aircraft weight and aircraft characteristics (e.g., enginethrust, wing configuration). Tagged up is the time at which airplane 19Ais acquired by TRACON surveillance and “tags up” on the radar scope.After tagged up, the airplane 19A proceeds to its departure fix and thenits meter point.

Some events or states shown in FIG. 1A may be detected by onboardsensors. For example, OFF may be detected by a sensor that actuates whenthe wheel struts are fully retracted or by a sensor that detects whenthe wheel well doors close. Events or states leading up to takeoff arenot so easily detected by current onboard sensors. In particular, eventsor states occurring in the airport's non-movement areas are not asamenable to accurate detection and monitoring by current onboardsensors.

Referring to an example of an aircraft (metered or not metered)preparing to depart an airport that does not have an automated surfacesurveillance system, prior to the assigned departure time the hereindisclosed aircraft surface event state track (ASSET) system detectsspecific events that define or relate to various possible states of theaircraft. For example, the system may detect events that indicate thedeparting aircraft has pushed back from its gate. The system may computea confidence level and/or interval that the occurrence of these eventswill result in the aircraft meeting its scheduled take-off time and thenmay provide a Traffic Management Coordinator (TMC) with a level ofconfidence or expectation that the aircraft will take off on time. Thesystem then may pass the aircraft surface state information to otherentities in a traffic management system.

In the above example, a departure reservoir coordinator (e.g., a Localair traffic controller) may use non-movement area surveillance providedby the aircraft surface state event track system to verify a flight willmeet its target movement area entry time (TMAT). If the airline providestarget off block times (TOBT), the departure reservoir coordinator coulduse the ramp area surveillance to determine whether a flight met itsTOBT and likely will meet its TMAT. If not, the departure reservoircoordinator may change the departure sequence to minimize missed runawayopportunities.

Instead of actively tracking the location of all aircraft in themovement area, the aircraft surface state event track system provides acost-effective approach for small/medium airports and for thenon-movement areas of all airports by tracking certain aircraft states.For a departing aircraft, these states may include when the aircraft:(1) pushes back from the gate, (2) starts taxiing, (3) stops taxiing,(4) enters an airport movement area, and (5) takes off. Knowing theaircraft's state at these discrete points in time can provide enoughinformation to compensate for a lack of surveillance. In an embodiment,the aircraft surface state event track system uses information fromexisting sensors in cockpit-based devices and uploads the data to anassociated cloud-based system. The associated cloud-based system thendetermines aircraft states in both the movement and non-movement areas,and may predict the likelihood that the aircraft will meet its departurewindow. This information may be monitored by other systems/operatorsthat implement strategic or tactical adjustments as needed to maintainairport and airspace efficiency.

Many air carriers have equipped their aircraft with Electronic FlightBags. Many Class 1 and Class 2 EFBs may include devices with multiplesensors. The aircraft surface state event track system may access thesensors to obtain a variety of data that may be used to determineaircraft state. In aircraft without an EFB, cockpit crews may use mobilephones with similar internal sensors. In either situation, the mobiledevices present in an airplane's cockpit should have a rich set ofsensors that may provide information that may be interpreted toascertain aircraft state. The mobile devices also provide a level ofredundancy, and the devices combine and process data (e.g., location,acceleration, velocity, compass heading, sound, and vibration) frommultiple sensors. For example, a mobile phone may have multiple sensorsthat can determine location (Wi-Fi, cellular, and GPS) and typicallyemploys software that “chooses” the method that provides a reasonableresult using the least amount of power (if running on battery). Accuracyof the location depends on the type sensor used and other factors suchas distance from transmitters, line of sight, and electromagneticinterference, for example. Motion of the mobile device is determined byaccelerometers and/or GPS. Microphones and other sensors built into thedevices can also be used by the aircraft surface state event tracksystem. For example, a comparison of acoustic signatures could determinewhen aircraft engines have been turned on or off.

In an embodiment, the aircraft surface state event track system includesa surface state event track system application and a surface state eventtrack system service. The aircraft surface state event track system mayuse “Portable” EFBs and mobile devices that can transmit their sensordata. An application (an aircraft surface state event track system App)running on a device may access the sensor data via the device'soperating system application programming interface (API). The sensordata may be securely transmitted to the surface state event track systemservice using a cellular link or another aircraft onboard datalink suchas SatCom. The surface state event track system service may becloud-based. Using the cloud means that servers and software are notrequired at each airport and additional resources can be inexpensivelyadded to support increases in demand and the number of airportsserviced.

The surface state event track system service analyzes the stream ofmobile sensor data in real-time to derive aircraft state and statechange events. Unlike a surveillance system, the surface state eventtrack system service does not need to “know” the precise location of theaircraft. For example, the service may use as inputs, (1) an approximateaircraft location compared to a mapping of the airport's terminals, and(2) a lack of movement to determine that an aircraft is parked at agate. The exact gate may not matter, just the fact that the aircraft isin a “gate state.” When movement is detected over a sustained period,the surface state event track system service may generate a gatepushback event. Supplemental information sources may provide additionaldata as needed. For example, FlightStats.com can be used to determinegate assignments.

The surface state event track system service may compare the derivedaircraft state information with key Traffic Flow Management (TFM) eventtimes (e.g., EOBT, TMAT, metering times) and calculate a confidenceinterval and level for those times. The surface state event track systemservice may transmit the confidence interval and level to theappropriate stakeholders to improve their performance. For example, toimprove arrival metering, the aircraft surface state event track systemconfidence of TBFM metering times may be sent to the TMC and airlineoperations center (AOC). Confidence values for TMATs may be provided tothe departure reservoir coordinator and AOC to avoid missed departureslots. For departures from airports within the freeze horizon to meteredairports, the aircraft surface state event track system may provideadvanced notice to the TMC that an aircraft will not make its metertime. This advanced notice allows the TMC to adjust the arrival sequenceand avoid “starving” the runway.

FIG. 1B illustrates a National Airspace System (NAS) environment inwhich an aircraft 19A departing airport 10 must enter a metered timeslot 32 en route 30 to arrival airport 10′. FIG. 1C illustrates theairport 10 in detail. FIG. 1D illustrates a logical flow of informationcorresponding to aircraft 19A's departure from airport 10 and travel toarrival airport 10′.

In FIG. 1B, airplane 19A is scheduled to depart airport 10 inside thefreeze horizon (i.e., an internal departure) and is given arrival slot32 within arrival stream 30 to TBFM destination airport 10′. Aircraft19A proceeds through several distinct and identifiable “states”,including, for example aircraft gate pushback 21, runway entry 23, andtake-off (OFF) 25 for entry into departure stream 20. During departure,aircraft 19A may be under control of Local air traffic control atairport 10, and TRACON 55. Aircraft 19A transitions to control in ARTCC35 and enters en route stream 30, slot 32, at the meter point. If thedeparture states occur as expected, the TMC's (e.g., TMC 51 at Center50) confidence that the airplane 19A will merge into the en route stream30 in the designated slot 32 is increased. If any of the departurestates are missed or are late, the TMC 51 (or a TMC at Center 60) mayhave additional time to change the arrival sequence 40 for the arrivalairport 10′ to support the internal departure of aircraft 19A fromairport 10. Aircraft surface state event track system 100 (see FIG. 2A)provides the Local air traffic control at airport 10, and by extension,the TMCs, an early indication of departure (e.g., gate pushback) andconfirmation of departure (e.g., takeoff).

FIG. 1C illustrates airport 10 in which an example aircraft surfacestate event track system (see FIG. 2A), and corresponding method, may beimplemented. In FIG. 1C, airport 10, which may be typical of many smallor mid-size airports, does not include surveillance systems found atlarge airports, such as surface or ground radar systems andmultilateration systems, for example. At airport 10, the hereindisclosed aircraft surface state event track system may provide the solesystem for tracking aircraft in non-movement areas. Those non-movementareas include at least the surface 13 (i.e., including a gate area)surrounding terminal 11, at which airplane 19A initially is parked(prior to gate pushback state 21). Also shown in FIG. 1C, airplane 19Amoves from the gate area to ramp 14A and stops at intersection 17Abefore proceeding with runway entry (state (23). Aircraft 19A thenproceeds with take-off, reaching OFF (state 25) and finally fix 27, atwhich point, aircraft 19A appears on air surveillance radar. Airportsurface state event track system Apps (not shown in FIG. 1B) installedon mobile devices onboard airplane 19A (and on each of airplanes 18A,19, and 19B), transmit signals (raw data and processed data) that may bereceived by the aircraft surface state event track system (also notshown in FIG. 1C). The surface state event track system service then maygenerate an advisory signal and message to alert Local airport controlpersonnel (i.e., at airport 10 and the center 50) as to the status ofeach of the aircraft and a confidence level that relevant ones of theaircraft will make their target event times (e.g., airplane 19A's OFFtime is within schedule).

FIG. 1D shows an example of information flow between and among theairplane 19A, the Centers 50 and 60, Local control at airports 10 and10′, and the aircraft surface state event track system. The airplane 19Aimplements components of the aircraft surface state event track system,mainly an application (App) 110 installed onboard the airplane 19A in,for example, mobile devices that may comprise a cockpit EFB (not shownin FIG. 1D). Remaining components of the aircraft surface state eventsystem are shown, in an embodiment, as implemented in the cloud, asservice 150.

Possible states of the airplane 19A are determined by the service 150based on signals received, and in some cases processed, through controlof the App 110. In an embodiment, the App 110 controls sensors and othercomponents in mobile device 103 to transmit raw signal data to theservice 150. For example, the App 110 may control the mobile device 103to send audio signals picked up by a microphone in the mobile device 103to the service 150. The App 110 also may control the mobile device 103to send processed information, such as position information received bya GPS receiver to the service 150. The service 150 processes thereceived information to determine different events associated with theairplane 19A, and from the events, to determine various states of theairplane 19A. For example, the service 150 may associate a soundsignature conforming to a signature for a jet engine as an indicationthe airplane 19A has its engines running, and a change of geographicalposition as an indication the airplane 19A is moving. The result ofthese processes is generation of a series of airplane states 21, 23, and25 along with associated start and stop time for each state. Assumingthe airplane 19A is departing the airport 10, the aircraft states shouldfollow a general pattern with times that correspond to estimated orscheduled times (e.g., EOBT) for the airplane 19A. The service 150 thenmay pass the airplane state information to Local air traffic control 10Aand to Center 50. The service 150 also may compute a confidence levelthat each of the required states to transition from gate to OFF willoccur within the scheduled or estimated times for each of these states.For metered aircraft, the Local air traffic control 10A may communicatewith the Center 50 to provide a call for release and receive aCoordinated Release Time (CRT). In an embodiment, the App 110 mayperform some of the computations and operations of the service 150.

In an example, the departure airport 10 and the arrival airport 10′ maybe under control of different Centers (50 and 60) and different TRACONs.In this example, the Centers 50 and 60 may communicate regarding theprogress of airplane 19A in its ascent to reach its meter point (slot 32in en route stream 30). Finally, the center 50 may provide meter pointdata to the Local air traffic control 10A′ for airport 10′.

A specific scenario in which the system 100 may improve schedulinginvolves a departing flight at a large airport without rampsurveillance. The aircraft needs to push back from the gate by a knowntime (based on ramp congestion and historical taxi times) to meet itsTMAT. The system 100 operates to determine that the aircraft has pushedback from the gate. Depending on subsequent sensor data, the system 100determines whether the aircraft pushed back and stopped (i.e., to recordan on-time departure) or started to taxi to the spot. The system 100notifies Local flight management personnel and systems that the TMATappears to be realistic based on this information. The system 100 alertslocal flight management personnel and systems when the system 100predicts the aircraft will miss its TMAT by more than a configurabletime, thereby allowing Local flight management personnel and systems toadjust the departure plan and recover the departure slot.

Another scenario involves a large storm system that causes widespreadairport capacity reductions and temporarily shuts down a hub airport.Inbound aircraft are diverted to other airports. Some of these airportslack surface surveillance. Some lack gates. The crews shut down theaircraft engines while they wait for the storm to pass. As the aircraftsit on the tarmacs, crew duty-time limits (FAR Part 117) become aconcern. The system 100 continues to automatically report the aircraftlocations providing the AOC with the basic, but critical, informationneeded to efficiently recover their operations.

FIG. 2A illustrates an example aircraft surface state event tracksystem. In an embodiment, aircraft surface state event track system 100is designed to determine aircraft surface states based on sensor datareceived from an aircraft onboard sensor suite, to predict a time fromfirst aircraft surface state to future aircraft surface states, tocompute a confidence level and interval that the aircraft's futuresurface states occur at the predicted or scheduled time, and to provideappropriate messaging and information to Local and Center flightmanagement systems and personnel regarding the current aircraft surfacestate, future surface states, and the confidence levels associated withthose future surface states. By performing as designed, the hereindisclosed aircraft surface state event track system allows flightmanagement personnel to assess if designated slots in departure, enroute, and arrival streams will be filled by a specific airplane. Forease of description, the herein disclosed aircraft surface state eventtrack system 100 is described as it relates to three specific aircraftsurface states, namely, gate pushback, runway entry, and takeoff.However, those skilled in the art will appreciate that the hereindisclosed aircraft surface state event track system 100 may be used tomonitor, define, evaluate and report any other possible aircraft surfacestates.

In addition, the description may refer to aircraft operating under atactical departure regime. However, the same or similar concepts wouldapply to any aircraft departure or arrival process or regime. The goal,in either tactical departure or non-tactical departure scenarios toprovide appropriate flight management personnel with information andconfidence that a specific aircraft will meet its intended takeoff timeand arrive on time at its designated slot in whatever stream that slotexists.

The aircraft surface state event track system 100, in an embodiment, mayoperate without any pilot, cockpit crew, or other aircraft crew(collectively, aircrew) actions. That is, the system 100 may operateautomatically and autonomously from the perspective of aircrew.Furthermore, the system 100 provides no outputs or information to theaircrew.

In FIG. 2A, aircraft surface state event track system 100 includessurface state event track App 110 and surface state event track systemservice 150. The App 110 is shown installed on table device 103, whichis a component of EFB 101. The App 110 also may be installed on othermobile devices, including mobile devices that are not components of anEFB. In an embodiment, only one mobile device and one App operate toprovide signals and information to the service. In another embodiment,the system 100 may use multiple mobile devices and multiple Apps toprovide signals and information to the service 150. The App 110 receivesinformation from sensors installed in the mobile device 103, includingvideo camera 121, GPS receiver 123, microphone 125, cellular receiver127, accelerometers 129, and other sensors. For example, the APP 110 mayreceive periodic GPS position updates from the GPS receiver 123. The App110 then may provide the information received from the sensors to theservice 150.

The service 150 is shown implemented as a cloud-based system, althoughother configurations and architectures are possible. In thisimplementation, the service 150 includes data store 155, aircraft dataanalysis module 160, airport data module 170, moving map module 175,state analysis module 180, and event time estimation module 190. In anembodiment, the service 150 further includes statistical analysis module200.

The service 150 receives and stores inputs that include airport data,aircraft data, signals data, airplane information, and flight managementdata, and outputs alerts and messages to AOCs and other airport andairline management systems and personnel. The airport data include a mapof the airport 10. The signals data include information and data such asGPS positions received from the mobile device 103. The aircraft datainclude aircraft identification and flight number as assigned by theairline. Airplane information includes design and configurationinformation for various aircraft types that may use the airport 10,including, for each aircraft type, number of engines, sound signaturefor the engines, operational characteristics, and other information. Theflight management data includes EOBT, TMAT, and other time-basedestimates assigned to a specific flight so that the flight reaches itsmeter point on time. The alerts and messages include aircraft statemessages such as a gate pushback state message and a confidence levelthat the next aircraft state (in this case, for example, runway entry)is achieved on schedule.

The data store 155 stores airplane information for aircraft that mayoperate out of the airport 10. The data store 155 also stores flightmanagement data for a specific flight. The data store 155 may storecompleted flight data such as actual time off block, OFF time, and otherdata to be used in system performance evaluation processes and airline,airplane, aircraft, and flight crew evaluation processes.

The aircraft analysis module 160 analyzes signals information (raw andprocessed) received from airplane 19A to determine the status ofairplane 19A. For example, the analysis module 160 may receive a soundsignature recorded by the microphone on the mobile device 103 and sentto the service 150. Most commercial aircraft use jet engines; a few usejet engines to drive a propeller, and still fewer use a cylinder andpiston arrangement to drive a propeller. Jet engines have acharacteristic sound signature that is known or knowable. Different jetengines have different sound signatures. The mobile device microphone125 may acquire or record the sound associated with jet engine start andlow speed operation and provide this sound recording to the service 150.The module 160 may compare the sound signature to specific airplane data(i.e., the sound signature for the specific make and model of theinstalled jet engines) for the airplane 19A and may determine theairplane 19A engines are at idle or are operating at a sufficiently highRPM that the airplane 19A should be moving on the surface of the airport19A. Alternately, and in the absence of a jet engine sound signature forcomparison, the module 160 may compare the recorded sound signature to ageneric jet engine sound signature to determine possible aircraftoperation. The module 160 may detect engine speed changes that indicatethe airplane is beginning to taxi, or is slowing and stopping. Usingrecorded sound signatures in comparison to known sound signatures allowsthe module 160 to determine possible engine operation. The module 160then may pass the identified possible engine operation to state analysismodule 180, where the engine operation information is considered withother information to assess aircraft state.

The airport data module 170 provides information related to a specificairport (i.e., the airport 10) from which the airplane 19A is soon todepart. The information may include a layout of the airport 10identifying gates, runways, taxiways, and ramps, for example.

The moving map module 175 may receive aircraft positional data from amoving map system installed in the EFB 101.

The state estimation module 180 receives a constant stream of inputsfrom other modules of the service 150 and executes a repetitiveoperation to determine if enough data are available to determine if theairplane 19A is progressing toward, has reached, or is leaving aspecific aircraft state. If the aircraft state is gate pushback,indications that the airplane 19A is approaching this state include anoise signature for jet engines of the airplane 19A, an access doorclosed sound recording and/or a recording of a flight public addressannouncement recorded public that the access door is closed, andancillary recorded announcements. Gate pushback also may be signaled bysignals from the accelerometers, GPS signals, and other information. Themodule 180 logic may include a simple algorithm in which each of thepossible inputs is weighted, and once a total value is reached, themodule 180 declares the airplane 19A has reached a specific state, inthis example, gate pushback.

The state time estimation module 190 estimates a time at which theairplane 19A will reach its next aircraft state; for example, the timefrom gate pushback to runway entry, and the time from runway entry toaircraft takeoff. The module 190 may base this information on specificairport data such as length of a taxiway from the airplane's position atgate pushback. The module 190 alternately or in addition, may base thistime estimation on historical averages, recorded in data store 155, forsuch movements. TOBT compared to engine start signal, door closed sound(which can be heard by a microphone on mobile device 103), cabinannouncement of door closed, can be used to determine if gate pushbackwill occur at the target time.

In making the above comparisons and time estimations, the modules 180and 190, respectively, may refer to historical data. Generally, allcomparisons and time estimations may be based on data specific to thedeparture airport (i.e., airport 10). In addition, the comparisons andestimations may involve more granular calculations, and the comparisonand time estimation algorithms may be modified to account for thefollowing, non-inclusive, list of factors: the specific airline; thespecific flight of the specific airline; time of year, time of day,season, holidays; weather; flights to specific airports (e.g., ORD,EWR); airport maintenance and system upgrades in progress or completed;and age of the aircraft.

The statistical analysis module 200 performs various statistical andprobability calculations. In an embodiment, the module 200 computes aconfidence interval (for given confidence levels) that each designatedstate in airplane 19A's departure sequence will be reached within aspecified time—i.e., EOBT at noon, TMAT at 12:10, OFF at 12:15, plus orminus any windows. For example, the module may compute 95% confidenceintervals for OFF times given historical data. If airplane 19A'sprogress toward takeoff falls outside the computer confidence level, theservice 150 may notify Local and Center flight management systems andpersonnel.

An example of one statistical process involves determining confidencelevel associated with an OFF time for airplane 19A. Assume airplane 19Ais assigned daily flight number 202 from airport 10 to airport 10′.Flight 202 makes its OFF time of 12:15 with the following variances, forten consecutive days: (−20 seconds (1)); (−5 seconds (1)); (+15 seconds(4)); (+45 seconds (1)); and (+120 seconds (3)). The mean OFF time is12:15 plus 44 seconds, and the standard deviation is 19.899 seconds. Ifthe desired confidence level is 95%, the acceptable confidence intervalis 44+/−2.989 seconds. That is, flight 202 will achieve an OFF state at12:15:44+/−2.989 seconds with a 95% confidence level.

The statistical analysis module 200 may execute more complex algorithmicoperations such as, for example, computing the Bayesian probability thatairplane 19A will meet its CRT given flight 19A achieved gate pushbackat its EOBT; probability airplane 19A will meet its CRT given flight 19Ameets its TMAT; probability airplane 19A will meet its TMAT givenairplane 19A meets its EOBT; etc. To improve estimations andpredictions, the service 150 may incorporate machine learningtechniques.

The service 150 may execute its various operations in real time or nearreal time. That is, for example, the service 150 may compute gatepushback state within, for example, two seconds after events indicatinggate pushback has or is occurring, and may compute a confidence level ofthe remaining designated aircraft states of airplane 19A within the sametwo seconds. The service 150 then may provide a gate pushback statemessage and confidence intervals for remaining aircraft states to Localair traffic control 10A and Center 50 traffic control.

The aircraft surface state event track system 100 provides an efficientand accurate indication of aircraft surface state, which may beparticularly useful during off-nominal situations like weather triggereddiversions to other airports. The system 100 may output information thatallows air traffic management personnel and systems to track aircraftsurface movement in the absence of dedicated non-movement area surfacesurveillance systems. Different surface state event track applicationsand different categories of airports may require different aircraftstates. Departure metering at large airports without ramp surveillancemay only need gate pushback and taxi start/stop states, while arrivalmetering may gain the most benefit from movement area entry and takeoffstates occurring at small airports. The system 100 preferably usesaircraft states that can automatically be determined from mobiledevices. While sensors in EFBs and other mobile devices provide a coreelement of the aircraft surface state event track system 100, the system100 may use any available sensor data, but preferably data that areaccurate, quickly accessible, and readily and rapidly transmitted. SincePortable EFBs are typically COTS devices, information about embeddedsensors should be readily available. For Portable EFBs, the system 100may use temporary connections the EFBs may have with the aircraft (e.g.,GPS, datalink). The system 100 includes App 110 that can access sensordata (e.g., location) and transmit it to the service 150. The service150 receives and logs data from the App 110. The App 110 also may logthe sensor data it accesses and transmits. Once the data are received bythe service 150, the service 150 can analyze the data to determineaircraft state. One concern is possible latency of the cellular networkfor the various situations and vehicle states. A few seconds of latencyshould not be a problem for most detected events, but a delay of 30seconds or a minute or more could be. The data may be supplemented withadditional information regarding aircraft events such as, for example,engines on, gate pushback, taxi start, taxi stop, spot out, wheels off,wheels on, runway exit, spot in, gate arrival, engines off. Some ofthese events require supplemental information such as airport surfacemaps (including gate, spot, and runway locations). The system 100 willnot necessarily need to “know” the aircraft's precise location relativeto specific airport resources such as gates, ramp areas, or holdingspots. The system 100 simply needs to “know” an approximate location andwhen its location changes beyond a configurable amount. This thresholdmay be set low enough to provide meaningful updates and high enough tominimize telecommunications costs. Likewise, updating taxi velocityinformation improves the accuracy of the prediction of whether anaircraft will meet its off-time, but the costs of increased updates mustbe weighed against the associated improvement in accuracy. While statechange information, such as gate pushback, alone provides a goodindication as to whether a flight will make its TMAT or takeoff window,a confidence parameter (level, interval) may provide a more quantitativeindication of the probability these will be achieved. To determine theconfidence levels associated with achieving key events. For a largeairport with a lot of surface traffic computing a takeoff time is achallenging problem. A more feasible use of the aircraft surface stateevent track system 100 could be to predict a takeoff time at a smallairport where the TMC has little to no information about the aircraftsurface state. Estimating taxi out time at a small airport is inherentlyeasier than a large airport. Likewise, at a large airport estimatingTMAT confidence intervals is easier than estimating takeoff timeconfidence intervals. Each air traffic management application mayinvolve use of statistical and probabilistic methods that areappropriate for predicting key future aircraft surface states. Weexplore a range of approaches, from simple nominal estimates to advancedmachine learning techniques, and capture the potential challenges andbenefits of each.

In executing its designed functions, the system 100 differs fromcurrent, non-surveillance tracking systems such as ACARS, which attemptto predict aircraft surface movement and position based on complexalgorithms that never receive ground-truth signals, and, as a result,are prone to significant errors and inaccuracies.

In an alternate embodiment (see FIG. 2B), an aircraft surface stateevent track system 100′ comprises only the surface state service 150. Inthis embodiment, the aircraft surface state event track system 100′, andspecifically the service 150, relies on whatever signals might bereceived from mobile devices operating in an EFB or otherwise operatedby cockpit personnel. Otherwise, operation of the aircraft surface stateevent track system 100′ is the same as that of the system 100.

In yet another alternative embodiment (see FIG. 2C), an aircraft surfacestate event track system 100″ comprises a non-transitory,computer-readable storage medium on which are encoded data and programsof instruction, the instructions when executed by a processor, causingthe processor to perform the operations disclosed above with respect tothe service 150 of the system 100.

In still another alternative embodiment (see FIG. 2D), an aircraftsurface state event track system 100′″ may include appropriate softwareand hardware components installed at Local airports and at Centers thatallow the airports and Centers two-way communication with the service150. For example, the system 100′″ may include a thin client program 55that a flight manager at a Center 50 may use to query the service 150and to receive replies from the service 150.

FIGS. 3A-3B illustrate example methods executed by the aircraft surfacestate event track system 100 of FIG. 2A. The disclosed example methodsrelate to a flight of airplane 19A from airport 10 to airport 10′. Moreparticularly, FIGS. 3A-3B illustrate example methods executed byprocessor 151 to determine and track aircraft states during an aircraftdeparture. In FIG. 3A, method 300 begins in block 310 when the service150 receives signals from mobile device 103 located on airplane 19A. Inblock 320, the service 150 verifies the identification of airplane 19Aand its associated flight (flight 202 from airport 10 to airport 10′).The verification may include a lookup by a search device executing onprocessor 151 of flight data in data store 155. The service 150 thenestablishes a unique case number and identification for the flight,identifies an expected sequence of aircraft states (gate pushback(EOBT), runway entry (TMAT) and takeoff (OFF). The method 300 then movesto block 330 and the service determines the departure is, or is not, atactical departure. In either case, the method moves to block 340 andthe service 150 monitors and identifies signals received from the mobiledevice 103. In block 340, the service 150 compares, where applicable,the received signals to known data in the data store 155 to identify thesignals (for example, engine start, engine spin up, access door closure)and to log the signals and their originating event. The service also mayreceive or calculate geographic position of airplane 19A, and determinewhen and if the airplane is moving. The method 300 then moves to block350 and the service 150 determines if the recorded/logged data andevents indicate an aircraft state. For example, the service may receiveaudio shown to correspond to jet engine low speed operation for airplane19A, a change in geographic position, acceleration of airplane 19A, andcompare the events to the EOBT to conclude the airplane has pushed-backfrom its gate. Similarly, the service 150 may detect signals, comparethe signals to expected events, and determine the airplane 19A hasreached the runway (TMAT). Finally, the service 150 may determine theairplane 19A is accelerating to takeoff.

In block 360, the service 150 confirms an aircraft state has beenreached, and sends a corresponding message or alert to Local and centerflight management. The service repeats block 360 until all aircraftsurface states have been confirmed and reported. In parallel with block360, the service 150 executes one or more statistical or probabilityroutines. The executed statistical and probability routines providestatistical data (e.g., confidence intervals and levels) and orprobability data (Bayesian probability) that an upcoming aircraftsurface state will occur at an expected (scheduled) time. The service150 provides the statistical/probability information with the message oralert. In block 370, the service 130 receives an OFF indication and oran indication of TRACON acquisition, and the method 300 moves to block380, where the processor 151 stores the data associated with flight 202of airplane 19A, and the method 300 then ends.

The preceding disclosure refers to flowcharts and accompanyingdescriptions to illustrate the embodiments represented in FIGS. 3A-3B.The disclosed devices, components, and systems contemplate using orimplementing any suitable technique for performing the stepsillustrated. Thus, FIGS. 3A-3B are for illustration purposes only andthe described or similar steps may be performed at any appropriate time,including concurrently, individually, or in combination. In addition,many of the steps in the flow chart may take place simultaneously and/orin different orders than as shown and described. Moreover, the disclosedsystems may use processes and methods with additional, fewer, and/ordifferent steps.

Embodiments disclosed herein can be implemented in digital electroniccircuitry, or in computer software, firmware, or hardware, including theherein disclosed structures and their equivalents. Some embodiments canbe implemented as one or more computer programs; i.e., one or moremodules of computer program instructions, encoded on computer storagemedium for execution by one or more processors. A computer storagemedium can be, or can be included in, a computer-readable storagedevice, a computer-readable storage substrate, or a random or serialaccess memory. The computer storage medium can also be, or can beincluded in, one or more separate physical components or media such asmultiple CDs, disks, or other storage devices. The computer readablestorage medium does not include a transitory signal.

The herein disclosed methods can be implemented as operations performedby a processor on data stored on one or more computer-readable storagedevices or received from other sources.

A computer program (also known as a program, module, engine, software,software application, script, or code) can be written in any form ofprogramming language, including compiled or interpreted languages,declarative or procedural languages, and it can be deployed in any form,including as a stand-alone program or as a module, component,subroutine, object, or other unit suitable for use in a computingenvironment. A computer program may, but need not, correspond to a filein a file system. A program can be stored in a portion of a file thatholds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub-programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

We claim
 1. An automatic and autonomous aircraft surface state eventtrack system, comprising: a mobile device installed on an aircraft, themobile device comprising: sensors to acquire information indicatingoperation of the aircraft on a surface of an airport, and a processor:executing an application to control the sensors and to receive theinformation therefrom and to process of the information; controlling amemory to record the processed information; and controlling atransmitter to transmit the processed information from the aircraft; anda service, remote from the aircraft and in communication with the mobiledevice, the service comprising a computer executing machine instructionsto: control a receiver to receive the information from the transmitter,identify the information received from the mobile device, compare theidentified information to known data for the aircraft, based on thecomparison, determine the aircraft is at a defined aircraft surfacestate, comprising: comparing digital audio data recorded at the mobiledevice with known sound profiles for the aircraft at the defined surfacestate; comparing aircraft motion data recorded at the mobile device withknown motion data for the aircraft at the defined surface state; anddesignating a defined surface state reached status based on thecomparisons, and direct transmission of an aircraft surface statereached message to Local and Center flight management.
 2. The system ofclaim 1, further comprising the computer executing a statistical routineand provide statistical data from the execution relating to anoccurrence of an expected upcoming aircraft surface state and directtransmission of the statistical data with the aircraft surface statereached message.
 3. The system of claim 1, wherein the mobile device isa Portable Electronic Flight Bag.
 4. The system of claim 1, wherein: themachine instructions are stored on a non-transitory, computer-readablestorage medium; and the computer and the non-transitory,computer-readable storage medium are components of a flight managementcenter cloud storage device installed at the flight management center.5. The system of claim 1, wherein the service receives an OFF indicationand in response the computer associates the OFF indication with flightand airplane information of the aircraft.
 6. The system of claim 1,wherein the computer determines the aircraft is scheduled as a tacticaldeparture.
 7. The system of claim 6, wherein the computer determines aconfidence interval for the coordinated release time of the tacticaldeparture.
 8. The system of claim 1, to compare the identifiedinformation to known data for the aircraft, the computer: comparesdigital audio data recorded at the mobile device with known soundprofiles for the aircraft at the defined surface state; and comparesaircraft motion data recorded at the mobile device with known motiondata for the aircraft, and wherein based on the comparison, the computerdetermines the aircraft is at a defined aircraft surface state.
 9. Thesystem of claim 8, wherein the computer identifies aircraft surfacesstates comprising gate pushback, runway entry and takeoff and computes aconfidence interval for one or more confidence levels for one or moredefined aircraft surface states.
 10. The system of claim 1, wherein themobile device acquires additional signals information including aircraftspeed and direction information.
 11. The system of claim 1, wherein noinformation acquired by and processed through the mobile device isprovided by the system to the aircraft's cockpit crew.